NEURAL NETWORK BASED ROBUST CONTROL OF AN AIRCRAFT

Ilker Tanyer, Enver Tatlicioglu, and Erkan Zergeroglu

References

  1. [1] B.L. Stevens and F.L. Lewis, Aircraft control and simulation (New York: John Wiley & Sons, 2003).
  2. [2] J.P. How, E. Frazzoli, and G. Chowdhary, Handbook of unmanned aerial vehicles (Berlin: Springer, 2012).
  3. [3] H.J. Asl, M. Yazdani, and J. Yoon, Vision–based tracking control of quadrotor using velocity of image features, International Journal of Robotics and Automation, 31(4), 2016, 301–309.
  4. [4] S. Islam, X.P. Liu, and A.E. Saddik, Adaptive sliding mode control of unmanned four rotor flying vehicle, International Journal of Robotics and Automation, 30(2), 2015.
  5. [5] Z.T. Dydek, A.M. Annaswamy, and E. Lavretsky, Adaptive control and the NASA X-15-3 flight revisited, IEEE Control Systems, 30(3), 2010, 32–48.
  6. [6] H.J. Asl, G. Oriolo, and H. Bolandi, An adaptive scheme for image-based visual servoing of an underactuated UAV, International Journal of Robotics and Automation, 29(1), 2014, 92–104.
  7. [7] A.J. Calise and R.T. Rysdyk, Nonlinear adaptive flight control using neural networks, IEEE Control Systems, 18(6), 1998, 14–25.
  8. [8] A.J. Calise, Neural networks in nonlinear aircraft flight control, IEEE Aerospace and Electronic Systems Magazine, 11(7), 1996, 5–10.
  9. [9] Y. Zou and Z. Zheng, Optimal control for vertical take-off and landing aircraft non-linear system by online kernel-based dual heuristic programming learning, IET Control Theory & Applications, 9(6), 2015, 981–987.
  10. [10] X.-J. Liu, F. Lara-Rosano, and C.W. Chan, Model–reference adaptive control based on neurofuzzy networks, IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 34(3), 2004, 302–309.
  11. [11] T. Dierks and S. Jagannathan, Output feedback control of a quadrotor UAV using neural networks, IEEE Transactions on Neural Networks, 21(1), 2010, 50–66.
  12. [12] J. Leitner, A.J. Calise, and J.V.R. Prasad, Analysis of adaptive neural networks for helicopter flight control, Journal of Guidance, Control, and Dynamics, 20(5), 1997, 972–979.
  13. [13] Y. Shin, Neural network based adaptive control for nonlinear dynamic regimes, Ph.D. Dissertation, Georgia Institute of Technology, Atlanta, GA, USA, 2005.
  14. [14] E.N. Johnson and A.J. Calise, Pseudo-control hedging: A new method for adaptive control, Workshop on Advances in Navigation, Guidance and Control Technology, Redstone Arsenal, Alabama, 2000, 1–2.
  15. [15] C. Schumacher and J.D. Johnson, PI control of a tailless fighter aircraft with dynamic inversion and neural networks, American Control Conf., San Diego, CA, USA, 1999, 4173–4177.
  16. [16] R.T. Rysdyk, F. Nardi, and A.J. Calise, Robust adaptive nonlinear flight control applications using neural networks, American Control Conf., San Diego, CA, USA, 1999, 2595– 2599.
  17. [17] W. Sun and Y.N. Wang, A robust robotic tracking controller based on neural network, International Journal of Robotics and Automation, 20(3), 2005.
  18. [18] J. Shin, H.J. Kim, Y. Kim, and W.E. Dixon, Asymptotic attitude tracking of the rotorcraft-based UAV via RISE feedback and NN feedforward, IEEE Int. Conf. on Decision and Control, Atlanta, GA, USA, 2010, 3694–3699.
  19. [19] J. Shin, H.J. Kim, Y. Kim, and W.E. Dixon, Autonomous flight of the rotorcraft-based UAV using RISE feedback and NN feedforward terms, IEEE Transactions on Control Systems Technology, 20(5), 2012, 1392–1399.
  20. [20] B. Xian, D.M. Dawson, M.S. de Queiroz, and J. Chen, A continuous asymptotic tracking control strategy for uncertain nonlinear systems, IEEE Transactions on Automatic Control, 49(7), 2004, 1206–1211.
  21. [21] P.M. Patre, W. MacKunis, C. Makkar, and W.E. Dixon, Asymptotic tracking for systems with structured and unstructured uncertainties, IEEE Transactions on Control Systems Technology, 16(2), 2008, 373–379.
  22. [22] W. MacKunis, Nonlinear control for systems containing input uncertainty via a Lyapunov-based approach, Ph.D. Dissertation, University of Florida, Gainesville, FL, USA, 2009.
  23. [23] A. Arapostathis, R.K. George, and M.K. Ghosh, On the controllability of a class of nonlinear stochastic systems, Systems & Control Letters, 44(1), 2001, 25–34.
  24. [24] X. Dong, B.M. Chen, G. Cai, H. Lin, and T.H. Lee, Development of a comprehensive software system for implementing cooperative software system for implementing control of multiple unmanned aerial vehicles, International Journal of Robotics and Automation, 26(1), 2011, 49–63.
  25. [25] H. Yu and R.W. Beard, A vision-based three-tiered path planning and collision avoidance scheme for miniature air vehicles, International Journal of Robotics and Automation, 30(5), 2015.
  26. [26] X. Li, Y. Dong, C. Luo, and Y. Tan, A method of aircraft target recognition based on LLE and HMM, International Journal of Robotics and Automation, 32(2), 2017.
  27. [27] Y. Wang, S. Wang, M. Tan, and J. Yu, Simultaneous arrival planning for multiple unmanned vehicles formation reconfiguration, International Journal of Robotics and Automation, 32(4), 2017.
  28. [28] P. He and S. Dai, Real–time stealth corridor path planning for fleets of unmanned aerial vehicles in low–altitude penetration, International Journal of Robotics and Automation, 30(1), 2015, 60–69.
  29. [29] Y. Yan, Z. Lv, and R. Zhang, Fault evaluation of unmanned aerial vehicles power system with an improved fuzzy group decision making, International Journal of Robotics and Automation, 33(3), 2018. 21
  30. [30] R.R. Costa, L. Hsu, A.K. Imai, and P. Kokotovic, Lyapunov-based adaptive control of MIMO systems, Automatica, 39(7), 2003, 1251–1257.
  31. [31] G. Tao, Adaptive control design and analysis (New York: John Wiley & Sons, 2003).
  32. [32] K. Hornik, M. Stinchcombe, and H. White, Multilayer feedforward networks are universal approximators, Neural Networks, 2(5), 1989, 359–366.
  33. [33] F.L. Lewis, Nonlinear network structures for feedback control, Asian Journal of Control, 1(4), 1999, 205–228.
  34. [34] Y.H. Kim and F.L. Lewis, High-level feedback control with neural networks (Singapore: World Scientific, 1998).
  35. [35] P.A. Ioannou and J. Sun, Stable and robust adaptive control (Englewood Cliffs, NJ, USA: Prentice Hall, 1995).
  36. [36] V. Stepanyan and A. Kurdila, Asymptotic tracking of uncertain systems with continuous control using adaptive bounding, IEEE Transactions on Neural Networks, 20(8), 2009, 1320– 1329.
  37. [37] H.K. Khalil, Nonlinear systems (Upper Saddle River, NJ, USA: Prentice Hall, 2002).
  38. [38] W. MacKunis, P.M. Patre, M.K. Kaiser, and W.E. Dixon, Asymptotic tracking for aircraft via robust and adaptive dynamic inversion methods, IEEE Transactions on Control Systems Technology, 18(6), 2010, 1448–1456.
  39. [39] Federal Aviation Administration, Federal aviation regulations. Part 25: Airworthiness standards: Transport category airplanes, Washington DC, WA, USA, 2002.
  40. [40] B. Bidikli, E. Tatlicioglu, A. Bayrak, and E. Zergeroglu, A new robust integral of sign of error feedback controller with adaptive compensation gain, IEEE Int. Conf. on Decision and Control, Florence, Italy, 2013, 3782–3787.
  41. [41] B. Bidikli, E. Tatlicioglu, and E. Zergeroglu, A self tuning RISE controller formulation, American Control Conf., Portland, OR, USA, 2014, 5608–5613.
  42. [42] I. Tanyer, E. Tatlicioglu, E. Zergeroglu, M. Deniz, A. Bayrak, and B. Ozdemirel, Robust output tracking control of an unmanned aerial vehicle subject to additive state–dependent disturbance, IET Control Theory & Applications, 10(14), 2016, 1612–1619.
  43. [43] M. Krstic, Delay compensation for nonlinear, adaptive, and PDE systems (Berlin: Springer, 2009).

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